Derivation of the superconducting gap equation for the noncentrosymmetric superconductor Li2Pt3B

We present here the mathematical background of our approach, presented in Phys. Rev. B 86, 134526 (2012) regarding the gap function and symmetry for the noncentrosymmetric (NCS) superconductor $Li_2Pt_3B$. As revealed by the experiment, this NCS superconductor gives rise to line nodes in the superconducting order parameter, which is responsible for many of its experimental behaviors. Owing to the enhanced d-character of the relevant bands that cross the Fermi level,the system gets weakly correlated. The nature and symmetry of this nodal behavior is explained from a microscopic viewpoint. In this article starting with an Hubbard model relevant for this NCS system by considering the effect of the onsite Coulomb repulsion on the pairing potential perturbatively, we extract the superconducting gap equation. Further analysis of this equation predicts a $s_\pm$ wave gap function with line nodes as the most promising candidate in the superconducting state.Comment: 7 pages, Proceeding versio

Ginzburg-Landau theory of noncentrosymmetric superconductors

The data of temperature dependent superfluid density $n_s(T)$ in Li$_2$Pd$_3$B and Li$_2$Pt$_3$B [Yuan {\it et al.}, \phrl97, 017006 (2006)] show that a sudden change of the slope of $n_s (T)$ occur at slightly lower than the critical temperature. Motivated by this observation, we microscopically derive the Ginzburg-Landau (GL) equations for noncentrosymmetric superconductors with Rashba type spin orbit interaction. Cooper pairing is assumed to occur between electrons only in the same spin split band and pair scattering is allowed to occur between two spin split bands. The GL theory of such a system predicts two transition temperatures, the higher of which is the conventional critical temperature $T_c$ while the lower one $T^*$ corresponds to the cross-over from a mixed singlet-triplet phase at lower temperatures to only spin-singlet or spin-triplet (depending on the sign of the interband scattering potential) phase at higher temperatures. As a consequence, $n_s (T)$ shows a kink at this cross-over temperature. We attribute the temperature at which sudden change of slope occurs in the observed $n_s (T)$ to the temperature $T^*$. This may also be associated with the observed kink in the penetration depth data of CePt$_3$Si. We have also estimated critical field near critical temperature.Comment: 7 pages, 1 figur

Relic density and PAMELA events in a heavy wino dark matter model with Sommerfeld effect

In a wino LSP scenario the annihilation cross section of winos gravitationally bound in galaxies can be boosted by a Sommerfeld enhancement factor which arises due to the ladder of exchanged W bosons between the initial states. The boost factor obtained can be in the range S ~ 10^4 if the mass is close to the resonance value of M ~ 4 TeV. In this paper we show that if one takes into account the Sommerfeld enhancement in the relic abundance calculation then the correct relic density is obtained for 4 TeV wino mass due to the enhanced annihilation after their kinetic decoupling. At the same time the Sommerfeld enhancement in the \chi \chi --> W^+ W^- annihilation channel is sufficient to explain the positron flux seen in PAMELA data without significantly exceeding the observed antiproton signal. We also show that (e^- + e^+) and gamma ray signals are broadly compatible with the Fermi-LAT observations. In conclusion we show that a 4 TeV wino DM can explain the positron and antiproton fluxes observed by PAMELA and at the same time give a thermal relic abundance of CDM consistent with WMAP observations.Comment: 24 pages, 12 figures, 1 table; title corrected in arxiv metadat

Higgsino Dark Matter in Nonuniversal Gaugino Mass Models

We study two simple and well motivated nonuniversal gaugino mass models, which predict higgsino dark matter. One can account for the observed dark matter relic density along with the observed Higgs boson mass of ~ 125 GeV over a large region of the parameter space of each model, corresponding to higgsino mass of ~ 1 TeV. In each case this parameter region covers the gluino mass range of 2-3 TeV, parts of which can be probed by the 14 TeV LHC experiments. We study these model predictions for LHC in brief and for dark matter detection experiments in greater detail.Comment: 35 pages, 11 figures, pdflatex, new references and a few relevant decay branching ratios added in two tables. Version to appear in Phys Rev

PS-Sim: A Framework for Scalable Simulation of Participatory Sensing Data

Emergence of smartphone and the participatory sensing (PS) paradigm have paved the way for a new variant of pervasive computing. In PS, human user performs sensing tasks and generates notifications, typically in lieu of incentives. These notifications are real-time, large-volume, and multi-modal, which are eventually fused by the PS platform to generate a summary. One major limitation with PS is the sparsity of notifications owing to lack of active participation, thus inhibiting large scale real-life experiments for the research community. On the flip side, research community always needs ground truth to validate the efficacy of the proposed models and algorithms. Most of the PS applications involve human mobility and report generation following sensing of any event of interest in the adjacent environment. This work is an attempt to study and empirically model human participation behavior and event occurrence distributions through development of a location-sensitive data simulation framework, called PS-Sim. From extensive experiments it has been observed that the synthetic data generated by PS-Sim replicates real participation and event occurrence behaviors in PS applications, which may be considered for validation purpose in absence of the groundtruth. As a proof-of-concept, we have used real-life dataset from a vehicular traffic management application to train the models in PS-Sim and cross-validated the simulated data with other parts of the same dataset.Comment: Published and Appeared in Proceedings of IEEE International Conference on Smart Computing (SMARTCOMP-2018